Whiteboard Challenge – UX Design Exercise
Overview
This whiteboard challenge explored how to improve the shopping experience in the Electronics category, focusing on supporting users during high-stakes purchase decisions.
Electronics purchases are often complex: users compare multiple products, evaluate technical specifications, and need a high level of confidence before completing a purchase. The goal of the exercise was to identify key friction points in the decision-making journey and propose solutions that would increase purchase confidence and ultimately improve conversion.
Problem Space
User
The primary user considered in this exercise was a mobile shopper purchasing electronics. This user typically:
compares multiple products before buying
is sensitive to price differences
needs to evaluate technical specifications
wants reassurance about product authenticity and seller credibility
Context
Electronics purchases involve a high level of decision complexity due to:
technical specification overload
high product prices
uncertainty about product authenticity
the need to compare multiple alternatives before deciding
Key Pain Points
Several friction points were identified in the current experience:
Difficulty comparing product specifications across listings
Too much technical information presented without clear prioritization
Low purchase confidence due to high product cost
Doubts about authenticity or seller credibility
These issues can lead to hesitation or abandonment during the purchase journey.
Solution Space
Purchase Decision Journey
The key decision-making flow was mapped as:
Browse → Product Page (PDP) → Compare → Decide → Add to Cart
Two major opportunities for intervention were identified within this journey:
Product comparison stage
Trust signals on the product page
Proposed Solutions
Product Comparison Tool
A comparison tool designed to help users quickly evaluate multiple products side-by-side.
Key features include:
side-by-side specification comparison
highlighted differences between products
a “best value” indicator to support decision making
direct call-to-action to add the selected product to the cart
This solution reduces cognitive load and helps users make faster, more confident decisions.
Trust and Authenticity Signals on the Product Page
To increase purchase confidence, additional trust indicators were introduced on the product detail page:
Verified seller badge
Authenticity guarantee
Clear warranty information
Visible customer reviews
These signals help address user concerns about product authenticity and seller reliability, which are particularly important in high-value purchases.
Impact & Delivery
Metrics
To evaluate the effectiveness of the solution, the following metrics were identified:
Conversion rate – primary KPI measuring successful purchases
Comparison tool usage – indicating adoption of the new feature
Time to purchase – measuring decision efficiency
Business Goals
The proposed solutions aim to support the following business outcomes:
increase overall conversion in the Electronics category
increase GMV through higher confidence in high-value purchases
reduce purchase hesitation during the decision phase
Stakeholders
Successful implementation would require collaboration across several teams:
Category owners – category insights and priorities
Product managers – roadmap and prioritization
Analytics – measurement and experimentation
Research – user insights and validation
Engineering – technical feasibility and implementation
Trade-offs
Several trade-offs were considered during the design process:
providing more product specifications vs maintaining interface simplicity
displaying trust signals vs maintaining UI clarity
supporting thorough evaluation vs enabling faster decision-making
Balancing decision support and usability was a key design challenge.
Risks
Potential risks identified include:
inconsistent or incorrect product specification data from sellers
excessive information leading to decision overload
overuse of trust badges reducing their perceived credibility
Scalability
The proposed comparison framework is designed to be scalable and extendable to other high-complexity categories such as:
appliances
gaming
automotive
Data & Iteration
The solution includes a feedback loop based on product analytics:
track comparison tool usage
identify decision bottlenecks in the purchase journey
iterate on specification visibility and decision-support features
A/B testing can be used to validate design decisions such as:
placement of the comparison feature
positioning of trust signals
depth of technical specification information